School of Medicine

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Current Research and Scholarly Interests
I refer you to my web page for detailed list of interests, projects and publications. In addition to pressing the link here, you can search "Russ Altman" on http://www.google.com/

Bio
Alison Callahan is a postdoctoral scholar at the Stanford Center for Biomedical Informatics and a member of the Shah Lab. Her research involves developing and applying informatics methods that enable translational discoveries in biomedicine.

Her research projects include RegenBase, a collaboration with the Miami Project to Cure Paralysis and Department of Computer Science at the University of Miami. RegenBase uses semantic technologies to aggregate and analyze experimental data in spinal cord injury research.

Alison completed her PhD in the Department of Biology at Carleton University in Ottawa, Canada. Her doctoral research focused on developing HyQue, a framework for representing and evaluating scientific hypotheses, and applying this framework to discover genes related to aging. She was also a developer for Bio2RDF, an open-source project to build and provide the largest network of Linked Data for the life sciences.

Current Research and Scholarly Interests
Our laboratory develops computational methods to better understand how living systems respond to chemical agents. We use semantic technologies to integrate and analyze large biomedical data and enable knowledge-based discoveries in biology, biochemistry and medicine.

Current Research and Scholarly Interests
My lab focuses on biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. We primarily use methods based on regularized linear regression to accomplish this. We primarily focus on applications in oncology and neuroscience.

Current Research and Scholarly Interests
My main research interests lie in computational image analysis of biomedical data. Specifically, I use computers to perform biomedical image analysis more efficiently and accurately.